Organizational closedown and the process of deconstruction and creativity

This paper outlines an analysis of how the deconstruction of organizational, management control and performance management structures affects performances and how workers make sense of enhanced efforts and practices of creativity, in a situation when facing a certainty of job loss as of the closedown of the organization. In this paper, we have shown that the deconstruction of structures generate positive performance outcomes, and that such relation is being mediated by workers identity. We have also shown that identity work under a process of organizational closedown generate certain creativity. By doing so, this paper contributes to the literature on creativity and deconstruction by developing an emergent model where workers identity mediates formal structures in relation to performance. This paper contributes to the literature on closedowns by extending its analytical and theoretical domains, proving alternative, yet complementary and mediating explanations to the causes of drivers to enhanced performances during the process of closedown.     

Social Contexts and Coping Strategies of Foreign Wives in Korea: Using a Conceptual Framework of Social Identity Theory

This study aimed to address the social contexts of Korean society in which diverse social interactions of foreign wives take place and to identify coping strategies to construct positive social identities. Social identities are often reconstructed as a result of dynamic interactions with various situations. Using the conceptual framework of social identity theory, this study attempted to uncover the social contexts that shape foreign wives' social identities. This study, using the qualitative approach, selected nine Filipino and Vietnamese participants who were married to Korean men. The data were collected by in‐depth interviews, a focus group with three Vietnamese participants, field notes, participant observation, and photo documents. In the section on study findings, this study addressed Korean social contexts, in which Korean government has been providing a variety of multicultural policies and services for helping foreign wives successfully adapt to Korea. This study also found various forms of stereotypes and discrimination against foreign wives and presented their discrimination experiences. Diverse ways to cope with such negative experiences are presented in the last section. Given the findings, the researcher suggests that policies and programs should promote foreign wives' integration in Korean society.     

Estimation for a first-order bifurcating autoregressive process with heavy-tail innovations

Asymptotics of an alternative extreme-value estimator for the autocorrelation parameter in a first-order bifurcating autoregressive (BAR) process with non-gaussian innovations are derived. This contrasts with traditional estimators whose asymptotic behavior depends on the central part of the innovation distribution. Within any BAR model, the main concern is addressing the complex dependency between generations. The inability of traditional methods to handle this dependency motivated an alternative procedure. With the combination of an extreme-value approach and a clever blocking argument, the dependency issue within the BAR process was resolved, which in turn allowed us to derive the limiting distribution for the proposed estimator through the use of regular variation and non-stationary point processes. Finally, the implications of our extreme-value approach are discussed with an extensive simulation study that not only assesses the reliability of our proposed estimate but also presents the findings for a new estimator of an unknown location parameter θ and its implications.     

Maximum likelihood estimation for generalized conditionally autoregressive models of spatial data

Conditionally autoregressive (CAR) models are often used to analyze a spatial process observed over a lattice or a set of irregular regions. The neighborhoods within a CAR model are generally formed deterministically using the inter-distances or boundaries between the regions. To accommodate directional and inherent anisotropy variation, a new class of spatial models is proposed that adaptively determines neighbors based on a bivariate kernel using the distances and angles between the centroid of the regions. The newly proposed model generalizes the usual CAR model in a sense of accounting for adaptively determined weights. Maximum likelihood estimators are derived and simulation studies are presented for the sampling properties of the estimates on the new model, which is compared to the CAR model. Finally the method is illustrated using a data set on the elevated blood lead levels of children under the age of 72 months observed in Virginia in the year of 2000.     

Estimation of parameters of SDE driven by fractional Brownian motion with polynomial drift

ABSTRACT

Strongly consistent and asymptotically normal estimators of the Hurst index and volatility parameters of solutions of stochastic differential equations with polynomial drift are proposed. The estimators are based on discrete observations of the underlying processes.     

The Risk of James–Stein and Lasso Shrinkage

This article compares the mean-squared error (or ?₂ risk) of ordinary least squares (OLS), James–Stein, and least absolute shrinkage and selection operator (Lasso) shrinkage estimators in simple linear regression where the number of regressors is smaller than the sample size. We compare and contrast the known risk bounds for these estimators, which shows that neither James–Stein nor Lasso uniformly dominates the other. We investigate the finite sample risk using a simple simulation experiment. We find that the risk of Lasso estimation is particularly sensitive to coefficient parameterization, and for a significant portion of the parameter space Lasso has higher mean-squared error than OLS. This investigation suggests that there are potential pitfalls arising with Lasso estimation, and simulation studies need to be more attentive to careful exploration of the parameter space.     

Composite Estimation for Single‐Index Models with Responses Subject to Detection Limits

We propose a semiparametric estimator for single‐index models with censored responses due to detection limits. In the presence of left censoring, the mean function cannot be identified without any parametric distributional assumptions, but the quantile function is still identifiable at upper quantile levels. To avoid parametric distributional assumption, we propose to fit censored quantile regression and combine information across quantile levels to estimate the unknown smooth link function and the index parameter. Under some regularity conditions, we show that the estimated link function achieves the non‐parametric optimal convergence rate, and the estimated index parameter is asymptotically normal. The simulation study shows that the proposed estimator is competitive with the omniscient least squares estimator based on the latent uncensored responses for data with normal errors but much more efficient for heavy‐tailed data under light and moderate censoring. The practical value of the proposed method is demonstrated through the analysis of a human immunodeficiency virus antibody data set.     

Rebuilding Relationships in a Transgender Family: The Stories of Parents of Japanese Transgender Children

This study considers the process by which parents accept their transgender children through an analysis of the stories of parents in Japan. The study also considers how the gender identity of parents is affected by their child and the discourses related to queer identities. The mothers were strongly motivated to understand their child and reconstructed the image and life stories of the child. Through these processes, the mothers came to reconsider their own gender identities in queer ways. In contrast, the fathers had a lack of motivation to understand their child, and their masculinity was not significantly influenced by deessentialism.     

Does National Identification Always Lead to Chauvinism? A Cross-national Analysis of Contextual Explanations

This study examines the premise that national identification inevitably leads citizens to endorse chauvinism in the international arena. It argues that the relationship between national identification and chauvinism is affected by three contextual factors: globalization, inter-state conflict, and social division. A multilevel analysis of cross-national survey data from the International Social Survey Program National Identity II (2003) was employed in order to observe these three contextual effects, the sample consisting of 33 countries. The results demonstrate that closer relations exist between national identification and chauvinism in more globalized countries. The effects of inter-state conflict vary according to the indices used to measure conflict. Those countries that experienced a large number of deaths during the 2000s and mobilized resources and personnel evinced a higher level of chauvinism. This effect is not evidenced by other measures of conflict, however. Social division did not affect the level of chauvinism or its relation with national identification. These findings are used to critically evaluate the notion that citizens who identify with their nation tend to be nationally chauvinistic.